The present invention relates generally to induction machine monitoring and, more particularly, to a method and apparatus for determining motor fault information in an induction machine.
Electric motors, such as three-phase AC induction motors, are used in a variety of commercial and industrial environments. Refrigeration systems, printing presses, assembly lines, and a myriad of other applications use such motors. Regardless of the application, timely detection of a motor fault is of the utmost importance. Generally, a motor fault is not detected until complete breakdown of the electric motor, thereby, creating a situation marred with undue cost, downtime delay and repairs, as well as, potential hazardous conditions. As a result, it is necessary to efficiently and effectively detect a motor fault.
It is desirable to determine when an induction machine such as a motor or generator is experiencing a mechanical or electrical problem before total failure occurs. A number of problems can lead to breakdown or premature failure of an induction machine. For example, electrical unbalances, misalignment, air gaps, and rotor unbalance can lead to improper operation of the induction machine. Other problems can arise as a result of a defect that is internal to the machine such as bearing failure, material and structural flaws introduced to the machine during manufacturing, and overheating.
Typical motor monitoring systems monitor the real power to an induction machine as an indicator of health/condition of the motor and its driven load. However, the real power delivered to an induction machine or motor depends on outside factors or considerations outside of the motor itself. Inspection of the real power delivered to the induction machine is often done to determine fault conditions attributable to the load on the machine as well as the machine itself. For example, monitoring of the frequency spectrum of real power of the induction machine for unexpected harmonics or disturbances to expected harmonics would provide fault information associated with a combination of the load and the motor. However, harmonics in the frequency spectrum of real power is believed a better indicator of load faults than internal motor faults. As such, it is difficult to discern faults attributable to the motor itself versus those faults attributed to the load or motor driven.
Accordingly, a number of methods have been developed to distinguish between an internal motor fault and a fault attributable to the load of the machine. One such method utilizes values of currents and voltages in the three phases of an induction machine to estimate current which is not substantially affected by load torque effects of the machine. This method compares an estimated current value with an actual current value to determine if a fault is present. As such, it is necessary to model operation of the induction machine, or alternatively, generate a set of baseline values that are common to more than one induction machine. However, generating baseline values that are not particular to a given machine fails to take into account the nuances in operation of each machine which can lead to improper or false detection of fault conditions. Additionally, this method requires the calculation of flux linkage in the motor which increases the complexity as well as cost of the condition monitoring system.
It would therefore be desirable to design a more efficient system to discern an internal motor fault in an induction machine.
The present invention is directed to a condition monitoring system for determining an internal motor fault in an induction machine overcoming the aforementioned drawbacks. In accordance therewith, voltage and current data are acquired from an induction machine in operation. From the voltage and current data, xe2x80x9cdxe2x80x9d and xe2x80x9cqxe2x80x9d axis voltages and xe2x80x9cdxe2x80x9d and xe2x80x9cqxe2x80x9d currents are calculated. The axis voltages and currents then undergo a reference frame transformation. From the transformed voltage and current values, instantaneous reactive and instantaneous real power delivered to the induction machine is determined. An inspection of the frequency spectrum of the instantaneous real power as well as the instantaneous reactive power is then used to ascertain load and motor fault information. Specifically, an analysis of the frequency spectrum of the instantaneous reactive power provides an indication of an internal motor fault whereas the frequency spectrum of the instantaneous real power would provide an indication of motor-driven or load faults.
Therefore, in accordance with one aspect of the present invention, a method of identifying load and motor fault information in a condition monitoring system is provided. The method includes the step of simultaneously sampling voltage and current data of an induction machine in operation. An indicator of reactive power is then determined from a portion of the sample voltage and current data. The method further includes the step of determining an internal motor fault using the indicator of reactive power.
In accordance with another aspect of the present invention, an induction motor monitoring system includes at least one voltage sensor and at least one current sensor as well as a controller connected to the at least one voltage and the at least one current sensors. The controller is configured to receive voltage and current data from the at least one voltage and at least one current sensor and determine instantaneous reactive power from the voltage and current data. The controller is further configured to generate a frequency spectrum for the instantaneous reactive power and determine a motor fault from at least the frequency spectrum.
In accordance with yet a further aspect of the present invention, an apparatus to distinguish between a motor fault and a load fault in an AC induction motor is provided. The apparatus includes at least two current sensors for obtaining at least two AC motor current signals and at least two voltage sensors for obtaining at least two AC motor voltage signals. An analog-to-digital converter is provided for converting the at least two AC motor signals to digitized current signals and the at least two AC motor voltage signals to digitized voltage signals. The apparatus further includes a microprocessor to receive the digitized signals and compare instantaneous reactive power values to a set of baseline reactive power values to determine a motor fault in the motor.
The present invention may be implemented with either hardware and/or software. As such, in another aspect of the invention, a computer readable storage medium having a computer program stored thereon is used to determine faults in an AC induction motor. The computer program represents a set of instructions that when executed by a computer causes the computer to monitor operation of an AC motor having a load thereon and known to be operating normally. The computer is then caused to determine baseline operation from the modeling. The set of instructions further causes the computer to acquire real-time voltage and real-time current data of the AC motor in operation and determine reactive power of the AC motor from the real-time voltage and real-time current data. The computer is then caused to compare the reactive power to the baseline operation and determine therefrom the presence of fault conditions in the AC motor.
In accordance with another aspect of the present invention, a motor fault detector for an AC induction motor includes means for acquiring voltage and current data of an AC motor in operation. The detector further includes means for determining instantaneous reactive power from the AC motor from the voltage and current data. Means for determining an internal fault in the AC motor from the instantaneous reactive power is also provided.
Various other features, objects and advantages of the present invention will be made apparent from the following detailed description and the drawings.